@inproceedings{PyTorch,
    Author = {Ansel, Jason and Yang, Edward and He, Horace and Gimelshein, Natalia and Jain, Animesh and Voznesensky, Michael and Bao, Bin and Bell, Peter and Berard, David and Burovski, Evgeni and Chauhan, Geeta and Chourdia, Anjali and Constable, Will and Desmaison, Alban and DeVito, Zachary and Ellison, Elias and Feng, Will and Gong, Jiong and Gschwind, Michael and Hirsh, Brian and Huang, Sherlock and Kalambarkar, Kshiteej and Kirsch, Laurent and Lazos, Michael and Lezcano, Mario and Liang, Yanbo and Liang, Jason and Lu, Yinghai and Luk, CK and Maher, Bert and Pan, Yunjie and Puhrsch, Christian and Reso, Matthias and Saroufim, Mark and Siraichi, Marcos Yukio and Suk, Helen and Suo, Michael and Tillet, Phil and Wang, Eikan and Wang, Xiaodong and Wen, William and Zhang, Shunting and Zhao, Xu and Zhou, Keren and Zou, Richard and Mathews, Ajit and Chanan, Gregory and Wu, Peng and Chintala, Soumith},
    Title = {{PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation}},
    Booktitle = {29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS '24)},
    Month = apr,
    Year = 2024,
    Publisher = {ACM},
    Doi = {10.1145/3620665.3640366},
    Url = {https://docs.pytorch.org/assets/pytorch2-2.pdf}
}

@misc{MMEngine,
    Author = {MMEngine Contributors},
    Title = {{OpenMMLab Foundational Library for Training Deep Learning Models}},
    Year = 2022,
    Month = sep,
    Url = {https://github.com/open-mmlab/mmengine},
    Note = {Release date: 2022-09-01; License: Apache-2.0}
}

@article{MONAI,
    Author = {Cardoso, M. Jorge and Li, Wenqi and Brown, Richard and Ma, Nic and Kerfoot, Eric and Wang, Yiheng and Murray, Benjamin and Myronenko, Andriy and Zhao, Can and Yang, Dong and Nath, Vishwesh and He, Yufan and Xu, Ziyue and Hatamizadeh, Ali and Zhu, Wentao and Liu, Yun and Zheng, Mingxin and Tang, Yucheng and Yang, Isaac and Zephyr, Michael and Hashemian, Behrooz and Alle, Sachidanand and Zalbagi Darestani, Mohammad and Budd, Charlie and Modat, Marc and Vercauteren, Tom and Wang, Guotai and Li, Yiwen and Hu, Yipeng and Fu, Yunguan and Gorman, Benjamin and Johnson, Hans and Genereaux, Brad and Erdal, Barbaros S. and Gupta, Vikash and Diaz-Pinto, Andres and Dourson, Andre and Maier-Hein, Lena and Jaeger, Paul F. and Baumgartner, Michael and Kalpathy-Cramer, Jayashree and Flores, Mona and Kirby, Justin and Cooper, Lee A.D. and Roth, Holger R. and Xu, Daguang and Bericat, David and Floca, Ralf and Zhou, S. Kevin and Shuaib, Haris and Farahani, Keyvan and Maier-Hein, Klaus H. and Aylward, Stephen and Dogra, Prerna and Ourselin, Sebastien and Feng, Andrew},
    Title = {{MONAI: An open-source framework for deep learning in healthcare}},
    Journal = {arXiv preprint},
    Archiveprefix = {arXiv},
    Eprint = {2211.02701},
    Doi = {10.48550/arXiv.2211.02701},
    Month = nov,
    Year = 2022,
    Url = {https://monai.io},
    Note = {Version: 1.5.0; Repository: https://github.com/Project-MONAI/MONAI; License: Apache-2.0}
}

@article{AbdomenCT1K,
    author={Ma, Jun and Zhang, Yao and Gu, Song and Zhu, Cheng and Ge, Cheng and Zhang, Yichi and An, Xingle and Wang, Congcong and Wang, Qiyuan and Liu, Xin and Cao, Shucheng and Zhang, Qi and Liu, Shangqing and Wang, Yunpeng and Li, Yuhui and He, Jian and Yang, Xiaoping},
    journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
    title={AbdomenCT-1K: Is Abdominal Organ Segmentation a Solved Problem?}, 
    year={2022},
    volume={44},
    number={10},
    pages={6695-6714},
    doi={10.1109/TPAMI.2021.3100536}
}

@article{CTSpine1K,
    Author = {Deng, Yang and Wang, Ce and Hui, Yuan and others},
    Title = {{CtSpine1k: A large-scale dataset for spinal vertebrae segmentation in computed tomography}},
    Journal = {arXiv preprint},
    Archiveprefix = {arXiv},
    Eprint = {2105.14711},
    Month = may,
    Year = 2021,
    Url = {https://arxiv.org/abs/2105.14711},
    Note = {arXiv preprint arXiv:2105.14711}
}

@article{FLARE22,
    author = {Jun Ma and Yao Zhang and Song Gu and Cheng Ge and Shihao Ma and Adamo Young and Cheng Zhu and Kangkang Meng and Xin Yang and Ziyan Huang and Fan Zhang and Wentao Liu and YuanKe Pan and Shoujin Huang and Jiacheng Wang and Mingze Sun and Weixin Xu and Dengqiang Jia and Jae Won Choi and Natália Alves and Bram de Wilde and Gregor Koehler and Yajun Wu and Manuel Wiesenfarth and Qiongjie Zhu and Guoqiang Dong and Jian He and the FLARE Challenge Consortium and Bo Wang},
    title = {Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge},
    year = {2023},
    journal = {arXiv preprint arXiv:2308.05862},
}

@book{FLARE23,
    Title = {Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT: MICCAI Challenge, FLARE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings},
    Editor = {Jun Ma and Bo Wang},
    Series = {Lecture Notes in Computer Science},
    Publisher = {Springer Cham},
    Year = 2024,
    Month = jul,
    Doi = {10.1007/978-3-031-58776-4},
    Url = {https://doi.org/10.1007/978-3-031-58776-4},
    Isbn = {978-3-031-58776-4},
    Note = {Softcover ISBN: 978-3-031-58775-7; Published: 01--02 July 2024; Series ISSN: 0302-9743; Series E-ISSN: 1611-3349; Edition: 1; Pages: XI, 364; Copyright: The Editor(s) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024}
}

@article{ImageTBAD,
    AUTHOR={Yao, Zeyang  and Xie, Wen  and Zhang, Jiawei  and Dong, Yuhao  and Qiu, Hailong  and Yuan, Haiyun  and Jia, Qianjun  and Wang, Tianchen  and Shi, Yiyi  and Zhuang, Jian  and Que, Lifeng  and Xu, Xiaowei  and Huang, Meiping },
    TITLE={ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection},
    JOURNAL={Frontiers in Physiology},
    VOLUME={Volume 12 - 2021},
    YEAR={2021},
    URL={https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.732711},
    DOI={10.3389/fphys.2021.732711},
    ISSN={1664-042X},
}

@misc{KiTS23-1,
    title={The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CT}, 
    author={Nicholas Heller and Fabian Isensee and Dasha Trofimova and Resha Tejpaul and Zhongchen Zhao and Huai Chen and Lisheng Wang and Alex Golts and Daniel Khapun and Daniel Shats and Yoel Shoshan and Flora Gilboa-Solomon and Yasmeen George and Xi Yang and Jianpeng Zhang and Jing Zhang and Yong Xia and Mengran Wu and Zhiyang Liu and Ed Walczak and Sean McSweeney and Ranveer Vasdev and Chris Hornung and Rafat Solaiman and Jamee Schoephoerster and Bailey Abernathy and David Wu and Safa Abdulkadir and Ben Byun and Justice Spriggs and Griffin Struyk and Alexandra Austin and Ben Simpson and Michael Hagstrom and Sierra Virnig and John French and Nitin Venkatesh and Sarah Chan and Keenan Moore and Anna Jacobsen and Susan Austin and Mark Austin and Subodh Regmi and Nikolaos Papanikolopoulos and Christopher Weight},
    year={2023},
    eprint={2307.01984},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@article{KiTS23-2,
    title={The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge},
    journal={Medical Image Analysis},
    volume={67},
    pages={101821},
    year={2021},
    issn={1361-8415},
    doi={10.1016/j.media.2020.101821},
    url={https://www.sciencedirect.com/science/article/pii/S1361841520301857},
    author={Nicholas Heller and Fabian Isensee and Klaus H. Maier-Hein and Xiaoshuai Hou and Chunmei Xie and Fengyi Li and Yang Nan and Guangrui Mu and Zhiyong Lin and Miofei Han and Guang Yao and Yaozong Gao and Yao Zhang and Yixin Wang and Feng Hou and Jiawei Yang and Guangwei Xiong and Jiang Tian and Cheng Zhong and Jun Ma and Jack Rickman and Joshua Dean and Bethany Stai and Resha Tejpaul and Makinna Oestreich and Paul Blake and Heather Kaluzniak and Shaneabbas Raza and Joel Rosenberg and Keenan Moore and Edward Walczak and Zachary Rengel and Zach Edgerton and Ranveer Vasdev and Matthew Peterson and Sean McSweeney and Sarah Peterson and Arveen Kalapara and Niranjan Sathianathen and Nikolaos Papanikolopoulos and Christopher Weight},
}

@article{TSD,
    Author = {Wasserthal, J. and Breit, H.-C. and Meyer, M.~T. and Pradella, M. and Hinck, D. and Sauter, A.~W. and Heye, T. and Boll, D. and Cyriac, J. and Yang, S. and Bach, M. and Segeroth, M.},
    Title = {{TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images}},
    Journal = {Radiology: Artificial Intelligence},
    Year = 2023,
    Doi = {10.1148/ryai.230024},
    Url = {https://doi.org/10.1148/ryai.230024}
}

@misc{BraTs24,
    title={The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI}, 
    author={Maria Correia de Verdier and Rachit Saluja and Louis Gagnon and Dominic LaBella and Ujjwall Baid and Nourel Hoda Tahon and Martha Foltyn-Dumitru and Jikai Zhang and Maram Alafif and Saif Baig and Ken Chang and Gennaro D'Anna and Lisa Deptula and Diviya Gupta and Muhammad Ammar Haider and Ali Hussain and Michael Iv and Marinos Kontzialis and Paul Manning and Farzan Moodi and Teresa Nunes and Aaron Simon and Nico Sollmann and David Vu and Maruf Adewole and Jake Albrecht and Udunna Anazodo and Rongrong Chai and Verena Chung and Shahriar Faghani and Keyvan Farahani and Anahita Fathi Kazerooni and Eugenio Iglesias and Florian Kofler and Hongwei Li and Marius George Linguraru and Bjoern Menze and Ahmed W. Moawad and Yury Velichko and Benedikt Wiestler and Talissa Altes and Patil Basavasagar and Martin Bendszus and Gianluca Brugnara and Jaeyoung Cho and Yaseen Dhemesh and Brandon K. K. Fields and Filip Garrett and Jaime Gass and Lubomir Hadjiiski and Jona Hattangadi-Gluth and Christopher Hess and Jessica L. Houk and Edvin Isufi and Lester J. Layfield and George Mastorakos and John Mongan and Pierre Nedelec and Uyen Nguyen and Sebastian Oliva and Matthew W. Pease and Aditya Rastogi and Jason Sinclair and Robert X. Smith and Leo P. Sugrue and Jonathan Thacker and Igor Vidic and Javier Villanueva-Meyer and Nathan S. White and Mariam Aboian and Gian Marco Conte and Anders Dale and Mert R. Sabuncu and Tyler M. Seibert and Brent Weinberg and Aly Abayazeed and Raymond Huang and Sevcan Turk and Andreas M. Rauschecker and Nikdokht Farid and Philipp Vollmuth and Ayman Nada and Spyridon Bakas and Evan Calabrese and Jeffrey D. Rudie},
    year={2024},
    eprint={2405.18368},
    archivePrefix={arXiv},
    primaryClass={cs.CV},
    url={https://arxiv.org/abs/2405.18368}, 
}

@article{CTORG,
    title={CT-ORG, a new dataset for multiple organ segmentation in computed tomography},
    author={Rister, Blaine and Yi, Darvin and Shivakumar, Kaushik and Nobashi, Tomomi and Rubin, Daniel L},
    journal={Scientific Data},
    volume={7},
    number={1},
    pages={381},
    year={2020},
    publisher={Nature Publishing Group UK London}
}

@article{LUNA16,
    title = {Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge},
    journal = {Medical Image Analysis},
    volume = {42},
    pages = {1-13},
    year = {2017},
    issn = {1361-8415},
    doi = {https://doi.org/10.1016/j.media.2017.06.015},
    url = {https://www.sciencedirect.com/science/article/pii/S1361841517301020},
    author = {Arnaud Arindra Adiyoso Setio and Alberto Traverso and Thomas {de Bel} and Moira S.N. Berens and Cas van den Bogaard and Piergiorgio Cerello and Hao Chen and Qi Dou and Maria Evelina Fantacci and Bram Geurts and Robbert van der Gugten and Pheng Ann Heng and Bart Jansen and Michael M.J. {de Kaste} and Valentin Kotov and Jack Yu-Hung Lin and Jeroen T.M.C. Manders and Alexander Sóñora-Mengana and Juan Carlos García-Naranjo and Evgenia Papavasileiou and Mathias Prokop and Marco Saletta and Cornelia M Schaefer-Prokop and Ernst T. Scholten and Luuk Scholten and Miranda M. Snoeren and Ernesto Lopez Torres and Jef Vandemeulebroucke and Nicole Walasek and Guido C.A. Zuidhof and Bram van Ginneken and Colin Jacobs}
}

@article{DA_Trans,
    title = {DA-TransUNet: integrating spatial and channel dual attention with transformer U-net for medical image segmentation},
    author = {Sun, Guanqun and Pan, Yizhi and Kong, Weikun and Xu, Zichang and Ma, Jianhua and Racharak, Teeradaj and Nguyen, Le-Minh and Xin, Junyi},
    journal = {Frontiers in Bioengineering and Biotechnology},
    volume = {12},
    pages = {1398237},
    year = {2024},
    publisher = {Frontiers Media SA}
}

@inproceedings{DconnNet,
    author = {Yang, Z. and Farsiu, S.},
    title = {Directional Connectivity-based Segmentation of Medical Images},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    pages = {11525--11535},
    year = {2023}
}

@article{DSNet,
    title={DSNet: A Novel Way to Use Atrous Convolutions in Semantic Segmentation},
    author={Guo, Zilu and Bian, Liuyang and Wei, Hu and Li, Jingyu and Ni, Huasheng and Huang, Xuan},
    journal={IEEE Transactions on Circuits and Systems for Video Technology},
    year={2024},
    publisher={IEEE}
}

@article{EffiFormer,
    title={Efficientformer: Vision transformers at mobilenet speed},
    author={Li, Yanyu and Yuan, Geng and Wen, Yang and Hu, Ju and Evangelidis, Georgios and Tulyakov, Sergey and Wang, Yanzhi and Ren, Jian},
    journal={Advances in Neural Information Processing Systems},
    volume={35},
    pages={12934--12949},
    year={2022}
}

@misc{EffiNet,
    title={EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks}, 
    author={Mingxing Tan and Quoc V. Le},
    year={2020},
    eprint={1905.11946},
    archivePrefix={arXiv},
    primaryClass={cs.LG},
    url={https://arxiv.org/abs/1905.11946}, 
}

@InProceedings{EGE,
    author="Ruan, Jiacheng
    and Xie, Mingye
    and Gao, Jingsheng
    and Liu, Ting
    and Fu, Yuzhuo",
    editor="Greenspan, Hayit
    and Madabhushi, Anant
    and Mousavi, Parvin
    and Salcudean, Septimiu
    and Duncan, James
    and Syeda-Mahmood, Tanveer
    and Taylor, Russell",
    title="EGE-UNet: An Efficient Group Enhanced UNet for Skin Lesion Segmentation",
    booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2023",
    year="2023",
    publisher="Springer Nature Switzerland",
    address="Cham",
    pages="481--490",
    abstract="Transformer and its variants have been widely used for medical image segmentation. However, the large number of parameter and computational load of these models make them unsuitable for mobile health applications. To address this issue, we propose a more efficient approach, the Efficient Group Enhanced UNet (EGE-UNet). We incorporate a Group multi-axis Hadamard Product Attention module (GHPA) and a Group Aggregation Bridge module (GAB) in a lightweight manner. The GHPA groups input features and performs Hadamard Product Attention mechanism (HPA) on different axes to extract pathological information from diverse perspectives. The GAB effectively fuses multi-scale information by grouping low-level features, high-level features, and a mask generated by the decoder at each stage. Comprehensive experiments on the ISIC2017 and ISIC2018 datasets demonstrate that EGE-UNet outperforms existing state-of-the-art methods. In short, compared to the TransFuse, our model achieves superior segmentation performance while reducing parameter and computation costs by 494x and 160x, respectively. Moreover, to our best knowledge, this is the first model with a parameter count limited to just 50KB. Our code is available at https://github.com/JCruan519/EGE-UNet.",
    isbn="978-3-031-43901-8"
}

@ARTICLE{LM_Net,
    author={Quan, Dou and Wang, Zhe and Lv, Chonghua and Wang, Shuang and Li, Yi and Ren, Bo and Chanussot, Jocelyn and Jiao, Licheng},
    journal={IEEE Transactions on Geoscience and Remote Sensing}, 
    title={LM-Net: A Lightweight Matching Network for Remote Sensing Image Matching and Registration}, 
    year={2024},
    volume={62},
    number={},
    pages={1-13},
    keywords={Image matching;Remote sensing;Feature extraction;Costs;Computational modeling;Learning systems;Accuracy;Optimization;Knowledge engineering;Representation learning;Deep features;feature distillation;feature relation distillation;image matching;image registration;lightweight network},
    doi={10.1109/TGRS.2024.3509638}
}

@InProceedings{MedNeXt,
    author="Roy, Saikat
    and Koehler, Gregor
    and Ulrich, Constantin
    and Baumgartner, Michael
    and Petersen, Jens
    and Isensee, Fabian
    and J{\"a}ger, Paul F.
    and Maier-Hein, Klaus H.",
    editor="Greenspan, Hayit
    and Madabhushi, Anant
    and Mousavi, Parvin
    and Salcudean, Septimiu
    and Duncan, James
    and Syeda-Mahmood, Tanveer
    and Taylor, Russell",
    title="MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation",
    booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2023",
    year="2023",
    publisher="Springer Nature Switzerland",
    address="Cham",
    pages="405--415",
    isbn="978-3-031-43901-8"
}

@INPROCEEDINGS{MoCo,
    author={He, Kaiming and Fan, Haoqi and Wu, Yuxin and Xie, Saining and Girshick, Ross},
    booktitle={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, 
    title={Momentum Contrast for Unsupervised Visual Representation Learning}, 
    year={2020},
    volume={},
    number={},
    pages={9726-9735},
    keywords={Dictionaries;Task analysis;Loss measurement;Unsupervised learning;Buildings;Visualization;Training},
    doi={10.1109/CVPR42600.2020.00975}
}

@INPROCEEDINGS{SegFormer3D,
    author={Perera, Shehan and Navard, Pouyan and Yilmaz, Alper},
    booktitle={2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)}, 
    title={SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation}, 
    year={2024},
    volume={},
    number={},
    pages={4981-4988},
    keywords={Training;Image segmentation;Solid modeling;Three-dimensional displays;Computational modeling;Computer architecture;Transformers;Segmentation;Transformers;Vision Transformers;ACDC;BraTs;Synapse;Attention;Efficient Attention;3D Medical Image Segmentation;Deep Learning},
    doi={10.1109/CVPRW63382.2024.00503}
}

@InProceedings{SwinUM,
    author="Liu, Jiarun
    and Yang, Hao
    and Zhou, Hong-Yu
    and Xi, Yan
    and Yu, Lequan
    and Li, Cheng
    and Liang, Yong
    and Shi, Guangming
    and Yu, Yizhou
    and Zhang, Shaoting
    and Zheng, Hairong
    and Wang, Shanshan",
    editor="Linguraru, Marius George
    and Dou, Qi
    and Feragen, Aasa
    and Giannarou, Stamatia
    and Glocker, Ben
    and Lekadir, Karim
    and Schnabel, Julia A.",
    title="Swin-UMamba: Mamba-Based UNet with ImageNet-Based Pretraining",
    booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024",
    year="2024",
    publisher="Springer Nature Switzerland",
    address="Cham",
    pages="615--625",
    isbn="978-3-031-72114-4"
}

@INPROCEEDINGS{UN3P,
    author={Huang, Huimin and Lin, Lanfen and Tong, Ruofeng and Hu, Hongjie and Zhang, Qiaowei and Iwamoto, Yutaro and Han, Xianhua and Chen, Yen-Wei and Wu, Jian},
    booktitle={ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
    title={UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation}, 
    year={2020},
    volume={},
    number={},
    pages={1055-1059},
    keywords={Image segmentation;Semantics;Computer architecture;Signal processing;Network architecture;Speech processing;Biomedical imaging;Segmentation;Full-scale skip connection;Deep supervision;Hybrid loss function;Classification.},
    doi={10.1109/ICASSP40776.2020.9053405}
}

@INPROCEEDINGS{UNETR,
    author={Hatamizadeh, Ali and Tang, Yucheng and Nath, Vishwesh and Yang, Dong and Myronenko, Andriy and Landman, Bennett and Roth, Holger R. and Xu, Daguang},
    booktitle={2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, 
    title={UNETR: Transformers for 3D Medical Image Segmentation}, 
    year={2022},
    volume={},
    number={},
    pages={1748-1758},
    keywords={Image segmentation;Three-dimensional displays;Semantics;Computer architecture;Transformers;Natural language processing;Decoding;Medical Imaging/Imaging for Bioinformatics/Biological and Cell Microscopy},
    doi={10.1109/WACV51458.2022.00181}
}

@article{VMamba,
    title={VMamba: Visual State Space Model},
    author={Liu, Yue and Tian, Yunjie and Zhao, Yuzhong and Yu, Hongtian and Xie, Lingxi and Wang, Yaowei and Ye, Qixiang and Liu, Yunfan},
    journal={arXiv preprint arXiv:2401.10166},
    year={2024}
}
